Results 51 to 60 of about 730,182 (230)
Advanced Intelligent Discovery, EarlyView.Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi +3 more
wiley +1 more source
International Journal of Robust and Nonlinear Control, EarlyView., 2023 Abstract We propose a hierarchical energy management scheme for aggregating Distributed Energy Resources (DERs) for grid flexibility services. To prevent a direct participation of numerous prosumers in the wholesale electricity market, aggregators, as self‐interest agents in our scheme, incentivize prosumers to provide flexibility. We firstly model the
Xiupeng Chen +3 more
wiley +1 more source
Journal of Applied Fluid Mechanics, 2011 In this study, two-dimensional inviscid compressible flow is solved around a moving solid body using Immersed Boundary Method (IBM) on a Cartesian grid.
S. Mohammad Hossein Karimian +1 more
doaj
Error-Correcting Codes from k-Resolving Sets
Discussiones Mathematicae Graph Theory, 2019 We demonstrate a construction of error-correcting codes from graphs by means of k-resolving sets, and present a decoding algorithm which makes use of covering designs.
Bailey Robert F., Yero Ismael G.
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Earth, Planets and Space, 2017 A simple and efficient finite-difference scheme is developed to calculate seismic wave propagation in a partial spherical shell model of a three-dimensionally (3-D) heterogeneous global Earth structure for modeling on regional or sub-global scales where ...
Hiroshi Takenaka +4 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia +2 more
wiley +1 more source
Mapping Proton‐Coupled Electron Transfer With Real Space Coordinates
Angewandte Chemie, EarlyView.We explore how proton‐coupled electron transfer (PCET) proceeds on a potential energy surface defined by two coordinates for proton and electron transfer that are obtained from quantum chemical calculations. The two‐dimensional maps for PCET show distinct characteristics for concerted proton–electron transfer and hydrogen atom transfer.
Adam Šrut +4 more
wiley +2 more sources
EngAccurate and efficient computation of partial inductances is essential in modern electromagnetic modeling. A three-dimensional cubic spline interpolation method is proposed for efficient evaluation of partial inductances between uniform cubic cells on a ...
Vjosa Shatri, Lavdim Kurtaj
doaj +1 more source
Toward Fully Soft and Multifunctional Shape Sensing via Optical Waveguide Arrays
Advanced Intelligent Systems, EarlyView.This work develops a sheet made with arrays of soft optical fibers that can reconstruct its 3D surface shape. Synergy of the waveguides’ responses to bending and pressing force allows shape reconstruction with resilience to damage. Applied onto surfaces of robotic or living systems, our design can be implemented in virtual reality, teleoperation ...
Qifan Yu, Nina Cao, Kaitlyn Becker
wiley +1 more source